Transformational Planning for Everyday Activity

We propose an approach to transformational planning and learning of everyday activity. This approach is targeted at autonomous robots that are to perform complex activities such as household chore. Our approach operates on flexible and reliable plans suited for long-term activity and applies plan transformations that generate competent and highperformance robot behavior. We show as a proof of concept that general transformation rules can be formulated that achieve substantially and significantly improved performance using table setting as an example.

• Type: Conference
• Year: 2007
• Where: AIPS
• Authors: Armin Müller, Alexandra Kirsch, Michael Beetz
• Keywords: AIPS 2007, Artificial Intelligence, Everyday Activity, General Transformation Rules, Transformational Planning